Health Technology/clinical-trials

Digital Post-Surgical Follow-Up Trial for Colorectal Cancer: Can the COLORECTUM+ Platform Transform Postoperative Care Quality?

247 Health News Editorial

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29 July 2026

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5 min read

·clinical-trials

A prospective Chinese trial is evaluating the COLORECTUM+ digital platform for postoperative colorectal cancer care, using mobile app-based symptom monitoring and real-time clinical alerts to improve follow-up rates and patient outcomes. Enrolling 236 surgical patients at Renji Hospital with a 52-week follow-up, the study could provide a replicable model for digital postoperative oncology care globally. Australian clinicians managing colorectal cancer patients should watch this space closely.

Originally reported by ClinicalTrials.gov

References

  1. 1.RenJi Hospital. (2024). Construction and application of a digital postoperative medical quality evaluation and promotion system for colorectal cancer based on the COLORECTUM+ model (NCT06685497). ClinicalTrials.gov. https://clinicaltrials.gov/study/NCT06685497
  2. 2.Sung, H., Ferlay, J., Siegel, R. L., Laversanne, M., Soerjomataram, I., Jemal, A., & Bray, F. (2021). Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA: A Cancer Journal for Clinicians, 71(3), 209–249. https://doi.org/10.3322/caac.21660
  3. 3.Australian Institute of Health and Welfare. (2023). Cancer in Australia 2023. AIHW. https://www.aihw.gov.au/reports/cancer/cancer-in-australia-2023
  4. 4.Basch, E., Deal, A. M., Dueck, A. C., Scher, H. I., Kris, M. G., Hudis, C., & Schrag, D. (2017). Overall survival results of a trial assessing patient-reported outcomes for symptom monitoring during routine cancer treatment. JAMA, 318(2), 197–198. https://doi.org/10.1001/jama.2017.7156
  5. 5.Moran, B., Brown, G., & Cunningham, C. (2021). Postoperative surveillance after colorectal cancer resection: current evidence and future directions. Colorectal Disease, 23(6), 1309–1318. https://doi.org/10.1111/codi.15517
  6. 6.Moghavem, N., Morrison, D., Bhatt, D. L., & Hernandez-Boussard, T. (2020). Surgical 30-day readmissions: a systematic review of machine learning approaches. JAMIA Open, 4(1), ooaa060. https://doi.org/10.1093/jamiaopen/ooaa060
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